{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Python Machine Learning 3rd Edition* by [Sebastian Raschka](https://sebastianraschka.com), Packt Publishing Ltd. 2019\n",
    "\n",
    "Code Repository: https://github.com/rasbt/python-machine-learning-book-3rd-edition\n",
    "\n",
    "Code License: [MIT License](https://github.com/rasbt/python-machine-learning-book-3rd-edition/blob/master/LICENSE.txt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python Machine Learning - Code Examples"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Chapter 5 - Compressing Data via Dimensionality Reduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the optional watermark extension is a small IPython notebook plugin that I developed to make the code reproducible. You can just skip the following line(s)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sebastian Raschka \n",
      "last updated: 2020-03-04 \n",
      "\n",
      "numpy 1.18.1\n",
      "scipy 1.4.1\n",
      "matplotlib 3.1.0\n",
      "sklearn 0.22\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -a \"Sebastian Raschka\" -u -d -p numpy,scipy,matplotlib,sklearn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*The use of `watermark` is optional. You can install this Jupyter extension via*  \n",
    "\n",
    "    conda install watermark -c conda-forge  \n",
    "\n",
    "or  \n",
    "\n",
    "    pip install watermark   \n",
    "\n",
    "*For more information, please see: https://github.com/rasbt/watermark.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- [Unsupervised dimensionality reduction via principal component analysis 128](#Unsupervised-dimensionality-reduction-via-principal-component-analysis-128)\n",
    "  - [The main steps behind principal component analysis](#The-main-steps-behind-principal-component-analysis)\n",
    "  - [Extracting the principal components step-by-step](#Extracting-the-principal-components-step-by-step)\n",
    "  - [Total and explained variance](#Total-and-explained-variance)\n",
    "  - [Feature transformation](#Feature-transformation)\n",
    "  - [Principal component analysis in scikit-learn](#Principal-component-analysis-in-scikit-learn)\n",
    "- [Supervised data compression via linear discriminant analysis](#Supervised-data-compression-via-linear-discriminant-analysis)\n",
    "  - [Principal component analysis versus linear discriminant analysis](#Principal-component-analysis-versus-linear-discriminant-analysis)\n",
    "  - [The inner workings of linear discriminant analysis](#The-inner-workings-of-linear-discriminant-analysis)\n",
    "  - [Computing the scatter matrices](#Computing-the-scatter-matrices)\n",
    "  - [Selecting linear discriminants for the new feature subspace](#Selecting-linear-discriminants-for-the-new-feature-subspace)\n",
    "  - [Projecting examples onto the new feature space](#Projecting-examples-onto-the-new-feature-space)\n",
    "  - [LDA via scikit-learn](#LDA-via-scikit-learn)\n",
    "- [Using kernel principal component analysis for nonlinear mappings](#Using-kernel-principal-component-analysis-for-nonlinear-mappings)\n",
    "  - [Kernel functions and the kernel trick](#Kernel-functions-and-the-kernel-trick)\n",
    "  - [Implementing a kernel principal component analysis in Python](#Implementing-a-kernel-principal-component-analysis-in-Python)\n",
    "    - [Example 1 – separating half-moon shapes](#Example-1:-Separating-half-moon-shapes)\n",
    "    - [Example 2 – separating concentric circles](#Example-2:-Separating-concentric-circles)\n",
    "  - [Projecting new data points](#Projecting-new-data-points)\n",
    "  - [Kernel principal component analysis in scikit-learn](#Kernel-principal-component-analysis-in-scikit-learn)\n",
    "- [Summary](#Summary)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import Image\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Unsupervised dimensionality reduction via principal component analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The main steps behind principal component analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 3,
     "metadata": {
      "image/png": {
       "width": 400
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(filename='images/05_01.png', width=400) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extracting the principal components step-by-step"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Class label</th>\n",
       "      <th>Alcohol</th>\n",
       "      <th>Malic acid</th>\n",
       "      <th>Ash</th>\n",
       "      <th>Alcalinity of ash</th>\n",
       "      <th>Magnesium</th>\n",
       "      <th>Total phenols</th>\n",
       "      <th>Flavanoids</th>\n",
       "      <th>Nonflavanoid phenols</th>\n",
       "      <th>Proanthocyanins</th>\n",
       "      <th>Color intensity</th>\n",
       "      <th>Hue</th>\n",
       "      <th>OD280/OD315 of diluted wines</th>\n",
       "      <th>Proline</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>14.23</td>\n",
       "      <td>1.71</td>\n",
       "      <td>2.43</td>\n",
       "      <td>15.6</td>\n",
       "      <td>127</td>\n",
       "      <td>2.80</td>\n",
       "      <td>3.06</td>\n",
       "      <td>0.28</td>\n",
       "      <td>2.29</td>\n",
       "      <td>5.64</td>\n",
       "      <td>1.04</td>\n",
       "      <td>3.92</td>\n",
       "      <td>1065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>13.20</td>\n",
       "      <td>1.78</td>\n",
       "      <td>2.14</td>\n",
       "      <td>11.2</td>\n",
       "      <td>100</td>\n",
       "      <td>2.65</td>\n",
       "      <td>2.76</td>\n",
       "      <td>0.26</td>\n",
       "      <td>1.28</td>\n",
       "      <td>4.38</td>\n",
       "      <td>1.05</td>\n",
       "      <td>3.40</td>\n",
       "      <td>1050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>13.16</td>\n",
       "      <td>2.36</td>\n",
       "      <td>2.67</td>\n",
       "      <td>18.6</td>\n",
       "      <td>101</td>\n",
       "      <td>2.80</td>\n",
       "      <td>3.24</td>\n",
       "      <td>0.30</td>\n",
       "      <td>2.81</td>\n",
       "      <td>5.68</td>\n",
       "      <td>1.03</td>\n",
       "      <td>3.17</td>\n",
       "      <td>1185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>14.37</td>\n",
       "      <td>1.95</td>\n",
       "      <td>2.50</td>\n",
       "      <td>16.8</td>\n",
       "      <td>113</td>\n",
       "      <td>3.85</td>\n",
       "      <td>3.49</td>\n",
       "      <td>0.24</td>\n",
       "      <td>2.18</td>\n",
       "      <td>7.80</td>\n",
       "      <td>0.86</td>\n",
       "      <td>3.45</td>\n",
       "      <td>1480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>13.24</td>\n",
       "      <td>2.59</td>\n",
       "      <td>2.87</td>\n",
       "      <td>21.0</td>\n",
       "      <td>118</td>\n",
       "      <td>2.80</td>\n",
       "      <td>2.69</td>\n",
       "      <td>0.39</td>\n",
       "      <td>1.82</td>\n",
       "      <td>4.32</td>\n",
       "      <td>1.04</td>\n",
       "      <td>2.93</td>\n",
       "      <td>735</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Class label  Alcohol  Malic acid   Ash  Alcalinity of ash  Magnesium  \\\n",
       "0            1    14.23        1.71  2.43               15.6        127   \n",
       "1            1    13.20        1.78  2.14               11.2        100   \n",
       "2            1    13.16        2.36  2.67               18.6        101   \n",
       "3            1    14.37        1.95  2.50               16.8        113   \n",
       "4            1    13.24        2.59  2.87               21.0        118   \n",
       "\n",
       "   Total phenols  Flavanoids  Nonflavanoid phenols  Proanthocyanins  \\\n",
       "0           2.80        3.06                  0.28             2.29   \n",
       "1           2.65        2.76                  0.26             1.28   \n",
       "2           2.80        3.24                  0.30             2.81   \n",
       "3           3.85        3.49                  0.24             2.18   \n",
       "4           2.80        2.69                  0.39             1.82   \n",
       "\n",
       "   Color intensity   Hue  OD280/OD315 of diluted wines  Proline  \n",
       "0             5.64  1.04                          3.92     1065  \n",
       "1             4.38  1.05                          3.40     1050  \n",
       "2             5.68  1.03                          3.17     1185  \n",
       "3             7.80  0.86                          3.45     1480  \n",
       "4             4.32  1.04                          2.93      735  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df_wine = pd.read_csv('https://archive.ics.uci.edu/ml/'\n",
    "                      'machine-learning-databases/wine/wine.data',\n",
    "                      header=None)\n",
    "\n",
    "# if the Wine dataset is temporarily unavailable from the\n",
    "# UCI machine learning repository, un-comment the following line\n",
    "# of code to load the dataset from a local path:\n",
    "\n",
    "# df_wine = pd.read_csv('wine.data', header=None)\n",
    "\n",
    "df_wine.columns = ['Class label', 'Alcohol', 'Malic acid', 'Ash',\n",
    "                   'Alcalinity of ash', 'Magnesium', 'Total phenols',\n",
    "                   'Flavanoids', 'Nonflavanoid phenols', 'Proanthocyanins',\n",
    "                   'Color intensity', 'Hue',\n",
    "                   'OD280/OD315 of diluted wines', 'Proline']\n",
    "\n",
    "df_wine.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Splitting the data into 70% training and 30% test subsets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X, y = df_wine.iloc[:, 1:].values, df_wine.iloc[:, 0].values\n",
    "\n",
    "X_train, X_test, y_train, y_test = \\\n",
    "    train_test_split(X, y, test_size=0.3, \n",
    "                     stratify=y,\n",
    "                     random_state=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Standardizing the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "sc = StandardScaler()\n",
    "X_train_std = sc.fit_transform(X_train)\n",
    "X_test_std = sc.transform(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "**Note**\n",
    "\n",
    "Accidentally, I wrote `X_test_std = sc.fit_transform(X_test)` instead of `X_test_std = sc.transform(X_test)`. In this case, it wouldn't make a big difference since the mean and standard deviation of the test set should be (quite) similar to the training set. However, as remember from Chapter 3, the correct way is to re-use parameters from the training set if we are doing any kind of transformation -- the test set should basically stand for \"new, unseen\" data.\n",
    "\n",
    "My initial typo reflects a common mistake is that some people are *not* re-using these parameters from the model training/building and standardize the new data \"from scratch.\" Here's simple example to explain why this is a problem.\n",
    "\n",
    "Let's assume we have a simple training set consisting of 3 examples with 1 feature (let's call this feature \"length\"):\n",
    "\n",
    "- train_1: 10 cm -> class_2\n",
    "- train_2: 20 cm -> class_2\n",
    "- train_3: 30 cm -> class_1\n",
    "\n",
    "mean: 20, std.: 8.2\n",
    "\n",
    "After standardization, the transformed feature values are\n",
    "\n",
    "- train_std_1: -1.21 -> class_2\n",
    "- train_std_2: 0 -> class_2\n",
    "- train_std_3: 1.21 -> class_1\n",
    "\n",
    "Next, let's assume our model has learned to classify examples with a standardized length value < 0.6 as class_2 (class_1 otherwise). So far so good. Now, let's say we have 3 unlabeled data points that we want to classify:\n",
    "\n",
    "- new_4: 5 cm -> class ?\n",
    "- new_5: 6 cm -> class ?\n",
    "- new_6: 7 cm -> class ?\n",
    "\n",
    "If we look at the \"unstandardized \"length\" values in our training datast, it is intuitive to say that all of these examples are likely belonging to class_2. However, if we standardize these by re-computing standard deviation and and mean you would get similar values as before in the training set and your classifier would (probably incorrectly) classify examples 4 and 5 as class 2.\n",
    "\n",
    "- new_std_4: -1.21 -> class 2\n",
    "- new_std_5: 0 -> class 2\n",
    "- new_std_6: 1.21 -> class 1\n",
    "\n",
    "However, if we use the parameters from your \"training set standardization,\" we'd get the values:\n",
    "\n",
    "- example5: -18.37 -> class 2\n",
    "- example6: -17.15 -> class 2\n",
    "- example7: -15.92 -> class 2\n",
    "\n",
    "The values 5 cm, 6 cm, and 7 cm are much lower than anything we have seen in the training set previously. Thus, it only makes sense that the standardized features of the \"new examples\" are much lower than every standardized feature in the training set.\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Eigendecomposition of the covariance matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Eigenvalues \n",
      "[4.84274532 2.41602459 1.54845825 0.96120438 0.84166161 0.6620634\n",
      " 0.51828472 0.34650377 0.3131368  0.10754642 0.21357215 0.15362835\n",
      " 0.1808613 ]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "cov_mat = np.cov(X_train_std.T)\n",
    "eigen_vals, eigen_vecs = np.linalg.eig(cov_mat)\n",
    "\n",
    "print('\\nEigenvalues \\n%s' % eigen_vals)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note**: \n",
    "\n",
    "Above, I used the [`numpy.linalg.eig`](http://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.eig.html) function to decompose the symmetric covariance matrix into its eigenvalues and eigenvectors.\n",
    "    <pre>>>> eigen_vals, eigen_vecs = np.linalg.eig(cov_mat)</pre>\n",
    "    This is not really a \"mistake,\" but probably suboptimal. It would be better to use [`numpy.linalg.eigh`](http://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.eigh.html) in such cases, which has been designed for [Hermetian matrices](https://en.wikipedia.org/wiki/Hermitian_matrix). The latter always returns real  eigenvalues; whereas the numerically less stable `np.linalg.eig` can decompose nonsymmetric square matrices, you may find that it returns complex eigenvalues in certain cases. (S.R.)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Total and explained variance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "tot = sum(eigen_vals)\n",
    "var_exp = [(i / tot) for i in sorted(eigen_vals, reverse=True)]\n",
    "cum_var_exp = np.cumsum(var_exp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "plt.bar(range(1, 14), var_exp, alpha=0.5, align='center',\n",
    "        label='Individual explained variance')\n",
    "plt.step(range(1, 14), cum_var_exp, where='mid',\n",
    "         label='Cumulative explained variance')\n",
    "plt.ylabel('Explained variance ratio')\n",
    "plt.xlabel('Principal component index')\n",
    "plt.legend(loc='best')\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_02.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Feature transformation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make a list of (eigenvalue, eigenvector) tuples\n",
    "eigen_pairs = [(np.abs(eigen_vals[i]), eigen_vecs[:, i])\n",
    "               for i in range(len(eigen_vals))]\n",
    "\n",
    "# Sort the (eigenvalue, eigenvector) tuples from high to low\n",
    "eigen_pairs.sort(key=lambda k: k[0], reverse=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matrix W:\n",
      " [[-0.13724218  0.50303478]\n",
      " [ 0.24724326  0.16487119]\n",
      " [-0.02545159  0.24456476]\n",
      " [ 0.20694508 -0.11352904]\n",
      " [-0.15436582  0.28974518]\n",
      " [-0.39376952  0.05080104]\n",
      " [-0.41735106 -0.02287338]\n",
      " [ 0.30572896  0.09048885]\n",
      " [-0.30668347  0.00835233]\n",
      " [ 0.07554066  0.54977581]\n",
      " [-0.32613263 -0.20716433]\n",
      " [-0.36861022 -0.24902536]\n",
      " [-0.29669651  0.38022942]]\n"
     ]
    }
   ],
   "source": [
    "w = np.hstack((eigen_pairs[0][1][:, np.newaxis],\n",
    "               eigen_pairs[1][1][:, np.newaxis]))\n",
    "print('Matrix W:\\n', w)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note**\n",
    "Depending on which version of NumPy and LAPACK you are using, you may obtain the Matrix W with its signs flipped. Please note that this is not an issue: If $v$ is an eigenvector of a matrix $\\Sigma$, we have\n",
    "\n",
    "$$\\Sigma v = \\lambda v,$$\n",
    "\n",
    "where $\\lambda$ is our eigenvalue,\n",
    "\n",
    "\n",
    "then $-v$ is also an eigenvector that has the same eigenvalue, since\n",
    "$$\\Sigma \\cdot (-v) = -\\Sigma v = -\\lambda v = \\lambda \\cdot (-v).$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2.38299011, 0.45458499])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train_std[0].dot(w)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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qquq/AniTiOwAsLl2+B9U9bEsXlhVL4nIhwA8DGAFgM+q6jNZnJsaKMnE/qvynmOiUovddXZdN4KhK4/gFNyewy8/BMCa7DrTYntQIrJKRIYB7AbwCoC/zio4+VT1QVX9VVV9raranZBfJnknMbDXQQ6JWyPU+9zSj6Ss14XZXLvPFvWG+O4D0A/gGIDbAHyikBZRS6zIPCpJZhtVQ3iBbXfnRvzG/z+Ehz8xkOviZVfLDxUpdogPwI2qugUAROQzAJ4opkmUFhdcEqUzsGVgybDa2BhwQ2DOya9VuG5ddsN8sUOLlpcfKlK9HtRF/y+qeqmAtlAL8tg2gcgmRY4OjI0tnXPyg1SWX/RcLT9UpHo9qJtExB+TEQCra/cFgKpqOYqRlUTwW96BA4tbJ5Rt2wSqJhOjA3kvXvZ7bLaWH7JBbKkjG7HUUWOqXlqsb2Eh4j9W2bL4qNTCBW3vvXf5fX4Bc1tcqaN6PShyTNy2Ccv+AzsShFgfjgCODlQZ94MqibJtmzA2trTdLDVTbVXYVJGWY4AqCRFvPH4olHk0NJRt5lER0iZ8WJFiT7mowqaKFEFVnbndfPPNSvUtLNS/74qFBdWhoaULqYaG4t/P6OjSx/3nj44W1WLKS/B3wf83Dt8ntwGY0ojPfPagSqYs2yY0M6TDFPtyK9PoADWHWXxkpWCQ8dWbFG/258umCgklVXiPVZVmw0IiI9IkfFR5Er0qCSVlGR2g5BigyDpphnSamUQvUzIFhzep1KImpmy9MUmiWpImfDQziV7GZIpmE0qIbAMmSZBrkg7pJO1xlbW3UeXhTSo3JklQaSSZRC9jMkUZ3xNVC5MkqPSS9LjK1ttIk1BC5AoGKKqUZpIpXMA1QlRmLBZLlRHubQSrYgPu9qTGxpYOZ/pBysX3QhTEAEWVEdfbANzvbXCNEJURkySocliRgMguTJIgqrGpt1GmRcNEWWOAIjKkKiWKiNIyEqBE5L+KyDMisiAiy7p1RGVX1kXDRFkylSRxHMCdAP7W0OsTGcVtzIkaM9KDUtWTqvpDE69NZIs8Fw1zbqs1vH52sH4OSkQGRWRKRKbm5+dNN4coM3ktGubcVmt4/eyRW4ASkUdE5HjE7d3NnEdVD6lqv6r2d3V15dVcokLlVaKIc1ut4fWzS25zUKr6jrzOTeS6vBYNJ5nb4jqweJwbtIvRhboi8i0AH1HVRKtvuVCXyiavYKEKtAXGRxYWvPOOjXk9gWCw2rvXC4pJhrCqEtzirh/lw6qFuiLy2yIyB+CNAP5BRB420Q4i0/JYNBw3t7Ww0NrwVVXmZspWUNhpUbsY2nrjjrpuS7pDLqXXaHfhy5fT7b7bzK7FLqvK+7QNYnbUZbFYyky94Z9Wh5ZsZduQV6O5rbY2735wc8MkcytVmZspc0FhJ0VFLVtv7EHZa3R06TdM/5vn6Gh5v5XWe8+mxfVWg9e+mR5U8DzB57r6b9cIe/vFQkwPyvp1UGQ/bZCaCyxuonfggPctPrgnk4vfShu9Z9PzFVFzW8E2pklt958flOXcTPg8Sc6b5jlJ2FRQuNKiopatN/ag7JXkm3nZvn232hsxIW2vL+9ecFy79u1b3o5W3wvZBzE9KONBp5kbA5Td6gUgFz/Mk3Ax6KYdvsorINQLfn19XmJH+PXKOmxcVQxQlKt6AaisHyZFBF3b5kLyak/Utezrq/87U9YvPVXEAEW5SRKATA7H5PGhWkTQrdoQVrg3miQl3sUeLC0XF6CYZk4tq5ea29m5WMFAdelzikiQyCu9Pe90ZA0kYQDeuYMJDupwBYdw2/3fi3ACxoc/DOzfH58S7/9bBu3d627iDUWIilq23tiDslv42+u+fWZ7AEX0cvIcgivjEFZUr3DPHtXt26P/nfxhvqoMG1cVOMRHRbLlA8T1D/kyDWHV+53Yvt0LVP77u3y58RxU1YZAy4wBigpnS3Bw9UPeluuXpUbJNEFJeuC2JZFQOnEBymg182axmrl7VM1WhdbA4lSfCwuEg+322xu+b3P762nmd0Ij5qtcfd8Uz6pq5uS+8PeaqO85/odsUJFVocMf8vUqJyR5P0WKS8IYGnK7JlyzvxOs6FBtzOKjpiXJjKvXAwCK6QEkzbQLv5+FBS+DzH8/pr61h1+7qMzHvNjwO0FuYYCipmjC9Oci0rCTDP00+pAPv5/OTuCrXwWmpxd7XcFgVbQy9SBYKZyaxTkoaloz8zrNzCE0E3SyXNsU9X76+oCjR73gVIZ5H5twXonCOAdFmQl+8/XFfXgn7QEk3a012OPJqop41PuZngZWrGBwykOZeoWULwYoalrWyQ/NBJ1gskBWW3dEvZ8gBqfs2ZaUQpaKyj239cZ1UObltQC32TU/Wa1tCrc/uEC0LGuPstbq2iMusKUwcMNCykJe6c/NDBtm2YMLvp/9+705p+lpbw5q377mNvSrgqRDsXHyGKKlEouKWrbe2IOyR9Yr+JP2oPLqwfl7Dvnf7i9dWvp6/Haf3bUvY4UMag1Y6ohs1ewHX9ZDROHz+ds8+OfjB+eirIKLq+WnKB9xAYrroMi4ZtfHZLmANTjkBHjnCaaWB1+HFq913BYYScQN0TIZhZaJilp53wB8HMAPADwN4MsA1iV5HntQ5Waq8CeHnJJr9VrZUuWe7ALLkiS+CWCzqm4F8CMAHzPUDrJIUetjNGIiPmmCRpX5PZ8ktQ3jlLXGIOXDyBCfqn4jcPcwgN9Je66LFy9ibm4OFy5caL1hOVm1ahU2bNiA9vZ2002pvKgqFMPDwJEjS3/O5iGn8LBj8H69x1o9d1alispWY5DyY8Mc1O8D+N9pnzw3N4eOjg709PRALPwNV1WcPn0ac3NzuP766003p9Ki5puGh4GDB737e/YAExN2FzCtV+YJaK0EVJISUlkFF1aToCRyC1Ai8giAqyMeGlHVr9R+ZgTAJQCTdc4zCGAQALq7u5c9fuHCBWuDEwCICNavX4/5+XnTTXFaqz0DYOk3/gMHFoPQ9u3ebWLC7gKmUQHWD6Z/9EdeWw8e9H4umOyxZ0/j61Xv3OFkEQYXKoqxYrEi8n4AfwBgp6qeS/KcqGKxJ0+eRG9vbw4tzJYr7bRRHsVhwxvmAa0HwCyCaJLXCBe29QPsvfcCb3rT0uHKPXu8P3/xFxtfq6hzsw4hFcGqYrEiciuAPwHwrqTBiaop+M0+i8oDcSnOYc1+ILdaYSGpqIob27d7Pae9e4Ft25Y+puo9luRaNVPNg6gQUal9ed8A/BjAswCma7e/SfK8qDTzEydOtJrh2LK77rpLu7q6dNOmTbE/Y0M7XZXl4tC86wjmnToddS22bVtePzB427MnWRuYbk+moKyVJJr64O/oiP4f3NGR/BwRvv3tb+vRo0cZoHKUVeWBvAqVZrE+KHw/fMyvcBE895498YGpmQDF9UlkUlyAsiGLrzgvvdTc8YTe+ta3YmZmpqVzUDzNsPJAXinOrVRYiJpje+Mbvccef3zxmF/INjgvNDHhPfaFLwAvvBB9/nAKfVz7udst2YbVzMlqfnBqZXFoWB5ZaHFBtFH7NGKOzV+XdeSI9/fgNejr86quB9ssEh2c9uzxsvuOHEnWlrGxpUHVD1ImtronAuxYB0UUy4Vv9uEgGkzRBpb2jKKy/KJS3/3su4MHF9dpRWXU+denr8/rXfn6+hazHNvakl8rppCTTRigyHq2Vx5IEkQbpcqHhwcnJrw//eAERL9nVeDMmaVDf/7i47e9Lf55RC5ggCIn2P7Nvl4QDQ7jAcsXwS4sePNLQcPDy18jat5NBOjsXB4c/aBp23UiakpU5oStN1uz+N7znvfo1VdfrStXrtRrr71WP/3pT7fWTjImr4rqcVl+jTLz/Ay8uIw6PyvR33DR/9l9+7JpN1ERwCw+AGfP5nLaBx54IJfzUrGyrlgRVC/LLzw8ODGxmHlXr/xSo55ZeM6LyDXVClBEMfL+sK+XKh81PPj444t/9/+MGt6LSrBgeSIqC6aZE2HpvkQHDniZb8GsvCyCU71U+ag5tiTzbmnLE4VTztOk6xPljQGKqCavWnR5btLnr5sK8tdOxSmqbiBRqxigiGrSLrZNIo9FsH7FiYMHvXVTCwvenwcPesej2h21MLiV4rtEeWKAIkI+FSvCbEiVz3MokyhrDFBEyHcYLi9+MoXfa2prW+xN+TX84p7HbTXIBZULUHlMDj/77LPYsWMHent7sWnTJhwI5hKTM1ysReenpQf5qelx8hzKJMpSpQJUXpPDK1euxCc/+UmcPHkShw8fxqc+9SmcOHGi1eaSATYMwzWj2WBTxFAmUVYqE6DynBy+5ppr8PrXvx4A0NHRgd7eXjz33HMZtZwoWqNg429lH/x5F4cyqboqs1C3qEWNMzMzePLJJ7F9+/ZsTkgUo16R2ulpr75fXFUMm4vvEvkq04MC8p8cfvnll7F7925MTExg7dq12ZyUqI6oebP9+73tNuqNFrg2lEnVVKkAlefk8MWLF7F7924MDAzgzjvvbP2ERAmFg0tbG1PJqRwqE6DynBxWVdx9993o7e3Fh8P7JhBlLEkmKlPJqQwqE6DynBz+7ne/i/vvvx+PPfYY+vr60NfXhwcffDC7xhPVJM1EZSo5lUFlkiSA/CaH3/KWt0D5P59ylrTietIt6IlsV6kABXBymNyVNBM1yRb0RC4Ql7759/f369TU1JJjJ0+eRG9vr6EWJedKO8l+ql7ig29hITrohLP1uIEh2UpEjqpqf/i4kTkoEfkfIvK0iEyLyDdE5FdMtIPINc3MLXG0gFxnKkni46q6VVX7AHwdwD5D7SByBssUUdUYmYNS1bOBu/8BAP9rETXAuSWqGmNJEiIyDuC/ATgDYEednxsEMAgA3d3dxTSOyFIsU0RVktsQn4g8IiLHI27vBgBVHVHV6wBMAvhQ3HlU9ZCq9qtqf1dXV17NbcmFCxewbds23HTTTdi0aRNGR0dNN4lKjHNLVBW5BShVfYeqbo64fSX0o/8LwO682hE2eWwSPRM9aLunDT0TPZg8NtnyOa+44go89thjeOqppzA9PY2HHnoIhw8fzqC1RETVZWSIT0Rep6r/t3b3XQB+UMTrTh6bxODXBnHu4jkAwOyZWQx+bRAAMLBlIPV5RQRXXnklAK8m38WLFyH8WuscpmUT2cVUFt9f1ob7ngbwmwCGinjRkUdHXg1OvnMXz2Hk0ZGWz3358mX09fXhNa95DXbt2sXtNhyT12aWRJSekQClqrtrw31bVfUOVS1kd79TZ041dbwZK1aswPT0NObm5vDEE0/g+PHjLZ+TipHnZpZElF6lSh11d3Zj9sxs5PGsrFu3DrfccgseeughbN68ObPzUn6K2sySiJpTmWrmADC+cxxr2tcsObamfQ3Gd463dN75+Xm8+OKLAIDz58/jkUcewQ033NDSOalY3J6CyD6VClADWwZw6I5D2Ni5EQLBxs6NOHTHoZYSJADg+eefx44dO7B161a84Q1vwK5du3D77bdn1GoqArenILJPpYb4AC9ItRqQwrZu3Yonn3wy03NScbg9BZGdKhegiMJYQojITgxQRGAJISIblWIOyvY9rWxvH3lYQojILs4HqFWrVuH06dPWBgFVxenTp7Fq1SrTTSEicorzQ3wbNmzA3Nwc5ufnTTcl1qpVq7BhwwbTzSAicorzAaq9vR3XX3+96WYQEVHGnB/iIyKicmKAIiIiKzFAERGRlcTW7LcoIjIPYHm112xdBeBnOb9GWfHapcdrlx6vXXq2XLuNqrpsy3SnAlQRRGRKVftNt8NFvHbp8dqlx2uXnu3XjkN8RERkJQYoIiKyEgPUcodMN8BhvHbp8dqlx2uXntXXjnNQRERkJfagiIjISgxQRERkJQaoOkTkIyKiInKV6ba4QkQ+LiI/EJGnReTLIrLOdJtsJyK3isgPReTHIvKnptvjChG5TkT+SUROisgzIjJkuk0uEZEVIvKkiHzddFviMEDFEJHrAOwCcMp0WxzzTQCbVXUrgB8B+Jjh9lhNRFYA+BSA2wDcCOC9InKj2VY54xKAP1bVXgC/DuCDvHZNGQJw0nQj6mGAincvgI8CYBZJE1T1G6p6qXb3MADuM1LfNpH4C6gAAALYSURBVAA/VtX/p6qvAPg7AO823CYnqOrzqvr92t9fgvdhe63ZVrlBRDYA+M8APm26LfUwQEUQkXcBeE5VnzLdFsf9PoB/NN0Iy10L4NnA/TnwQ7ZpItID4NcAHDHbEmdMwPsCvmC6IfU4vx9UWiLyCICrIx4aAfBnAH6z2Ba5o961U9Wv1H5mBN4QzGSRbXNQ1Mby7LU3QUSuBPBFAMOqetZ0e2wnIrcD+KmqHhWRW0y3p57KBihVfUfUcRHZAuB6AE+JCOANUX1fRLap6gsFNtFacdfOJyLvB3A7gJ3KhXaNzAG4LnB/A4CfGGqLc0SkHV5wmlTVL5lujyPeDOBdIvJOAKsArBWRz6vq7xlu1zJcqNuAiMwA6FdVGyr+Wk9EbgWwH8DbVHXedHtsJyIr4SWT7ATwHIDvAfhdVX3GaMMcIN43yPsA/FxVh023x0W1HtRHVPV2022JwjkoytpfAegA8E0RmRaRvzHdIJvVEko+BOBheJP8f8/glNibAbwPwNtrv2vTtV4BlQR7UEREZCX2oIiIyEoMUEREZCUGKCIishIDFBERWYkBioiIrMQARVQgEblcS4c+LiJfEJE1teNXi8jfici/iMgJEXlQRH414vmfFZGfisjx4ltPVCwGKKJinVfVPlXdDOAVAH9QW3D6ZQDfUtXXquqN8Mpt/XLE8z8H4NbCWktkUGVLHRFZ4P8A2ApgB4CLqvrqomZVnY56gqp+p1YYlaj02IMiMqBW4ug2AMcAbAZw1GyLiOzDAEVUrNUiMg1gCt5mmJ8x3B4ia3GIj6hY51W1L3hARJ4B8DuG2kNkLfagiMx7DMAVIvIB/4CIvEFE3mawTUTGMUARGVbbM+u3AeyqpZk/A2AMEftCicgDAB4H8J9EZE5E7i60sUQFYjVzIiKyEntQRERkJQYoIiKyEgMUERFZiQGKiIisxABFRERWYoAiIiIrMUAREZGV/h1VL7vg+pG9sQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_train_pca = X_train_std.dot(w)\n",
    "colors = ['r', 'b', 'g']\n",
    "markers = ['s', 'x', 'o']\n",
    "\n",
    "for l, c, m in zip(np.unique(y_train), colors, markers):\n",
    "    plt.scatter(X_train_pca[y_train == l, 0], \n",
    "                X_train_pca[y_train == l, 1], \n",
    "                c=c, label=l, marker=m)\n",
    "\n",
    "plt.xlabel('PC 1')\n",
    "plt.ylabel('PC 2')\n",
    "plt.legend(loc='lower left')\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_03.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Principal component analysis in scikit-learn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**NOTE**\n",
    "\n",
    "The following four code cells has been added in addition to the content to the book, to illustrate how to replicate the results from our own PCA implementation in scikit-learn:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.36951469, 0.18434927, 0.11815159, 0.07334252, 0.06422108,\n",
       "       0.05051724, 0.03954654, 0.02643918, 0.02389319, 0.01629614,\n",
       "       0.01380021, 0.01172226, 0.00820609])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "\n",
    "pca = PCA()\n",
    "X_train_pca = pca.fit_transform(X_train_std)\n",
    "pca.explained_variance_ratio_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(range(1, 14), pca.explained_variance_ratio_, alpha=0.5, align='center')\n",
    "plt.step(range(1, 14), np.cumsum(pca.explained_variance_ratio_), where='mid')\n",
    "plt.ylabel('Explained variance ratio')\n",
    "plt.xlabel('Principal components')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "pca = PCA(n_components=2)\n",
    "X_train_pca = pca.fit_transform(X_train_std)\n",
    "X_test_pca = pca.transform(X_test_std)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(X_train_pca[:, 0], X_train_pca[:, 1])\n",
    "plt.xlabel('PC 1')\n",
    "plt.ylabel('PC 2')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib.colors import ListedColormap\n",
    "\n",
    "def plot_decision_regions(X, y, classifier, resolution=0.02):\n",
    "\n",
    "    # setup marker generator and color map\n",
    "    markers = ('s', 'x', 'o', '^', 'v')\n",
    "    colors = ('red', 'blue', 'lightgreen', 'gray', 'cyan')\n",
    "    cmap = ListedColormap(colors[:len(np.unique(y))])\n",
    "\n",
    "    # plot the decision surface\n",
    "    x1_min, x1_max = X[:, 0].min() - 1, X[:, 0].max() + 1\n",
    "    x2_min, x2_max = X[:, 1].min() - 1, X[:, 1].max() + 1\n",
    "    xx1, xx2 = np.meshgrid(np.arange(x1_min, x1_max, resolution),\n",
    "                           np.arange(x2_min, x2_max, resolution))\n",
    "    Z = classifier.predict(np.array([xx1.ravel(), xx2.ravel()]).T)\n",
    "    Z = Z.reshape(xx1.shape)\n",
    "    plt.contourf(xx1, xx2, Z, alpha=0.4, cmap=cmap)\n",
    "    plt.xlim(xx1.min(), xx1.max())\n",
    "    plt.ylim(xx2.min(), xx2.max())\n",
    "\n",
    "    # plot examples by class\n",
    "    for idx, cl in enumerate(np.unique(y)):\n",
    "        plt.scatter(x=X[y == cl, 0], \n",
    "                    y=X[y == cl, 1],\n",
    "                    alpha=0.6, \n",
    "                    color=cmap(idx),\n",
    "                    edgecolor='black',\n",
    "                    marker=markers[idx], \n",
    "                    label=cl)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Training logistic regression classifier using the first 2 principal components."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "pca = PCA(n_components=2)\n",
    "X_train_pca = pca.fit_transform(X_train_std)\n",
    "X_test_pca = pca.transform(X_test_std)\n",
    "\n",
    "lr = LogisticRegression(multi_class='ovr', random_state=1, solver='lbfgs')\n",
    "lr = lr.fit(X_train_pca, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_decision_regions(X_train_pca, y_train, classifier=lr)\n",
    "plt.xlabel('PC 1')\n",
    "plt.ylabel('PC 2')\n",
    "plt.legend(loc='lower left')\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_04.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_decision_regions(X_test_pca, y_test, classifier=lr)\n",
    "plt.xlabel('PC 1')\n",
    "plt.ylabel('PC 2')\n",
    "plt.legend(loc='lower left')\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_05.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.36951469, 0.18434927, 0.11815159, 0.07334252, 0.06422108,\n",
       "       0.05051724, 0.03954654, 0.02643918, 0.02389319, 0.01629614,\n",
       "       0.01380021, 0.01172226, 0.00820609])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pca = PCA(n_components=None)\n",
    "X_train_pca = pca.fit_transform(X_train_std)\n",
    "pca.explained_variance_ratio_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Supervised data compression via linear discriminant analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Principal component analysis versus linear discriminant analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 23,
     "metadata": {
      "image/png": {
       "width": 400
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(filename='images/05_06.png', width=400) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The inner workings of linear discriminant analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Computing the scatter matrices"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculate the mean vectors for each class:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MV 1: [ 0.9066 -0.3497  0.3201 -0.7189  0.5056  0.8807  0.9589 -0.5516  0.5416\n",
      "  0.2338  0.5897  0.6563  1.2075]\n",
      "\n",
      "MV 2: [-0.8749 -0.2848 -0.3735  0.3157 -0.3848 -0.0433  0.0635 -0.0946  0.0703\n",
      " -0.8286  0.3144  0.3608 -0.7253]\n",
      "\n",
      "MV 3: [ 0.1992  0.866   0.1682  0.4148 -0.0451 -1.0286 -1.2876  0.8287 -0.7795\n",
      "  0.9649 -1.209  -1.3622 -0.4013]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "np.set_printoptions(precision=4)\n",
    "\n",
    "mean_vecs = []\n",
    "for label in range(1, 4):\n",
    "    mean_vecs.append(np.mean(X_train_std[y_train == label], axis=0))\n",
    "    print('MV %s: %s\\n' % (label, mean_vecs[label - 1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compute the within-class scatter matrix:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Within-class scatter matrix: 13x13\n"
     ]
    }
   ],
   "source": [
    "d = 13 # number of features\n",
    "S_W = np.zeros((d, d))\n",
    "for label, mv in zip(range(1, 4), mean_vecs):\n",
    "    class_scatter = np.zeros((d, d))  # scatter matrix for each class\n",
    "    for row in X_train_std[y_train == label]:\n",
    "        row, mv = row.reshape(d, 1), mv.reshape(d, 1)  # make column vectors\n",
    "        class_scatter += (row - mv).dot((row - mv).T)\n",
    "    S_W += class_scatter                          # sum class scatter matrices\n",
    "\n",
    "print('Within-class scatter matrix: %sx%s' % (S_W.shape[0], S_W.shape[1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Better: covariance matrix since classes are not equally distributed:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Class label distribution: [41 50 33]\n"
     ]
    }
   ],
   "source": [
    "print('Class label distribution: %s' \n",
    "      % np.bincount(y_train)[1:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scaled within-class scatter matrix: 13x13\n"
     ]
    }
   ],
   "source": [
    "d = 13  # number of features\n",
    "S_W = np.zeros((d, d))\n",
    "for label, mv in zip(range(1, 4), mean_vecs):\n",
    "    class_scatter = np.cov(X_train_std[y_train == label].T)\n",
    "    S_W += class_scatter\n",
    "print('Scaled within-class scatter matrix: %sx%s' % (S_W.shape[0],\n",
    "                                                     S_W.shape[1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compute the between-class scatter matrix:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Between-class scatter matrix: 13x13\n"
     ]
    }
   ],
   "source": [
    "mean_overall = np.mean(X_train_std, axis=0)\n",
    "d = 13  # number of features\n",
    "S_B = np.zeros((d, d))\n",
    "for i, mean_vec in enumerate(mean_vecs):\n",
    "    n = X_train_std[y_train == i + 1, :].shape[0]\n",
    "    mean_vec = mean_vec.reshape(d, 1)  # make column vector\n",
    "    mean_overall = mean_overall.reshape(d, 1)  # make column vector\n",
    "    S_B += n * (mean_vec - mean_overall).dot((mean_vec - mean_overall).T)\n",
    "\n",
    "print('Between-class scatter matrix: %sx%s' % (S_B.shape[0], S_B.shape[1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Selecting linear discriminants for the new feature subspace"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Solve the generalized eigenvalue problem for the matrix $S_W^{-1}S_B$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "eigen_vals, eigen_vecs = np.linalg.eig(np.linalg.inv(S_W).dot(S_B))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note**:\n",
    "    \n",
    "Above, I used the [`numpy.linalg.eig`](http://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.eig.html) function to decompose the symmetric covariance matrix into its eigenvalues and eigenvectors.\n",
    "    <pre>>>> eigen_vals, eigen_vecs = np.linalg.eig(cov_mat)</pre>\n",
    "    This is not really a \"mistake,\" but probably suboptimal. It would be better to use [`numpy.linalg.eigh`](http://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.eigh.html) in such cases, which has been designed for [Hermetian matrices](https://en.wikipedia.org/wiki/Hermitian_matrix). The latter always returns real  eigenvalues; whereas the numerically less stable `np.linalg.eig` can decompose nonsymmetric square matrices, you may find that it returns complex eigenvalues in certain cases. (S.R.)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sort eigenvectors in descending order of the eigenvalues:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Eigenvalues in descending order:\n",
      "\n",
      "349.6178089059939\n",
      "172.76152218979388\n",
      "3.7853134512521556e-14\n",
      "2.117398448224407e-14\n",
      "1.5164618894178885e-14\n",
      "1.5164618894178885e-14\n",
      "1.3579567140455979e-14\n",
      "1.3579567140455979e-14\n",
      "7.587760371654683e-15\n",
      "5.906039984472233e-15\n",
      "5.906039984472233e-15\n",
      "2.256441978569674e-15\n",
      "0.0\n"
     ]
    }
   ],
   "source": [
    "# Make a list of (eigenvalue, eigenvector) tuples\n",
    "eigen_pairs = [(np.abs(eigen_vals[i]), eigen_vecs[:, i])\n",
    "               for i in range(len(eigen_vals))]\n",
    "\n",
    "# Sort the (eigenvalue, eigenvector) tuples from high to low\n",
    "eigen_pairs = sorted(eigen_pairs, key=lambda k: k[0], reverse=True)\n",
    "\n",
    "# Visually confirm that the list is correctly sorted by decreasing eigenvalues\n",
    "\n",
    "print('Eigenvalues in descending order:\\n')\n",
    "for eigen_val in eigen_pairs:\n",
    "    print(eigen_val[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tot = sum(eigen_vals.real)\n",
    "discr = [(i / tot) for i in sorted(eigen_vals.real, reverse=True)]\n",
    "cum_discr = np.cumsum(discr)\n",
    "\n",
    "plt.bar(range(1, 14), discr, alpha=0.5, align='center',\n",
    "        label='Individual \"discriminability\"')\n",
    "plt.step(range(1, 14), cum_discr, where='mid',\n",
    "         label='Cumulative \"discriminability\"')\n",
    "plt.ylabel('\"Discriminability\" ratio')\n",
    "plt.xlabel('Linear discriminants')\n",
    "plt.ylim([-0.1, 1.1])\n",
    "plt.legend(loc='best')\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_07.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matrix W:\n",
      " [[-0.1481 -0.4092]\n",
      " [ 0.0908 -0.1577]\n",
      " [-0.0168 -0.3537]\n",
      " [ 0.1484  0.3223]\n",
      " [-0.0163 -0.0817]\n",
      " [ 0.1913  0.0842]\n",
      " [-0.7338  0.2823]\n",
      " [-0.075  -0.0102]\n",
      " [ 0.0018  0.0907]\n",
      " [ 0.294  -0.2152]\n",
      " [-0.0328  0.2747]\n",
      " [-0.3547 -0.0124]\n",
      " [-0.3915 -0.5958]]\n"
     ]
    }
   ],
   "source": [
    "w = np.hstack((eigen_pairs[0][1][:, np.newaxis].real,\n",
    "              eigen_pairs[1][1][:, np.newaxis].real))\n",
    "print('Matrix W:\\n', w)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Projecting examples onto the new feature space"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_train_lda = X_train_std.dot(w)\n",
    "colors = ['r', 'b', 'g']\n",
    "markers = ['s', 'x', 'o']\n",
    "\n",
    "for l, c, m in zip(np.unique(y_train), colors, markers):\n",
    "    plt.scatter(X_train_lda[y_train == l, 0],\n",
    "                X_train_lda[y_train == l, 1] * (-1),\n",
    "                c=c, label=l, marker=m)\n",
    "\n",
    "plt.xlabel('LD 1')\n",
    "plt.ylabel('LD 2')\n",
    "plt.legend(loc='lower right')\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_08.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## LDA via scikit-learn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA\n",
    "\n",
    "lda = LDA(n_components=2)\n",
    "X_train_lda = lda.fit_transform(X_train_std, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "lr = LogisticRegression(multi_class='ovr', random_state=1, solver='lbfgs')\n",
    "lr = lr.fit(X_train_lda, y_train)\n",
    "\n",
    "plot_decision_regions(X_train_lda, y_train, classifier=lr)\n",
    "plt.xlabel('LD 1')\n",
    "plt.ylabel('LD 2')\n",
    "plt.legend(loc='lower left')\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_09.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_test_lda = lda.transform(X_test_std)\n",
    "\n",
    "plot_decision_regions(X_test_lda, y_test, classifier=lr)\n",
    "plt.xlabel('LD 1')\n",
    "plt.ylabel('LD 2')\n",
    "plt.legend(loc='lower left')\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_10.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using kernel principal component analysis for nonlinear mappings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 37,
     "metadata": {
      "image/png": {
       "width": 500
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(filename='images/05_11.png', width=500) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementing a kernel principal component analysis in Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.spatial.distance import pdist, squareform\n",
    "from scipy.linalg import eigh\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "from distutils.version import LooseVersion as Version\n",
    "from scipy import __version__ as scipy_version\n",
    "\n",
    "\n",
    "if scipy_version >= Version('1.4.1'):\n",
    "    from numpy import exp\n",
    "else:\n",
    "    from scipy import exp\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def rbf_kernel_pca(X, gamma, n_components):\n",
    "    \"\"\"\n",
    "    RBF kernel PCA implementation.\n",
    "\n",
    "    Parameters\n",
    "    ------------\n",
    "    X: {NumPy ndarray}, shape = [n_examples, n_features]\n",
    "        \n",
    "    gamma: float\n",
    "      Tuning parameter of the RBF kernel\n",
    "        \n",
    "    n_components: int\n",
    "      Number of principal components to return\n",
    "\n",
    "    Returns\n",
    "    ------------\n",
    "     X_pc: {NumPy ndarray}, shape = [n_examples, k_features]\n",
    "       Projected dataset   \n",
    "\n",
    "    \"\"\"\n",
    "    # Calculate pairwise squared Euclidean distances\n",
    "    # in the MxN dimensional dataset.\n",
    "    sq_dists = pdist(X, 'sqeuclidean')\n",
    "\n",
    "    # Convert pairwise distances into a square matrix.\n",
    "    mat_sq_dists = squareform(sq_dists)\n",
    "\n",
    "    # Compute the symmetric kernel matrix.\n",
    "    K = exp(-gamma * mat_sq_dists)\n",
    "\n",
    "    # Center the kernel matrix.\n",
    "    N = K.shape[0]\n",
    "    one_n = np.ones((N, N)) / N\n",
    "    K = K - one_n.dot(K) - K.dot(one_n) + one_n.dot(K).dot(one_n)\n",
    "\n",
    "    # Obtaining eigenpairs from the centered kernel matrix\n",
    "    # scipy.linalg.eigh returns them in ascending order\n",
    "    eigvals, eigvecs = eigh(K)\n",
    "    eigvals, eigvecs = eigvals[::-1], eigvecs[:, ::-1]\n",
    "\n",
    "    # Collect the top k eigenvectors (projected examples)\n",
    "    X_pc = np.column_stack([eigvecs[:, i]\n",
    "                            for i in range(n_components)])\n",
    "\n",
    "    return X_pc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example 1: Separating half-moon shapes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from sklearn.datasets import make_moons\n",
    "\n",
    "X, y = make_moons(n_samples=100, random_state=123)\n",
    "\n",
    "plt.scatter(X[y == 0, 0], X[y == 0, 1], color='red', marker='^', alpha=0.5)\n",
    "plt.scatter(X[y == 1, 0], X[y == 1, 1], color='blue', marker='o', alpha=0.5)\n",
    "\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_12.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "\n",
    "scikit_pca = PCA(n_components=2)\n",
    "X_spca = scikit_pca.fit_transform(X)\n",
    "\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(7, 3))\n",
    "\n",
    "ax[0].scatter(X_spca[y == 0, 0], X_spca[y == 0, 1],\n",
    "              color='red', marker='^', alpha=0.5)\n",
    "ax[0].scatter(X_spca[y == 1, 0], X_spca[y == 1, 1],\n",
    "              color='blue', marker='o', alpha=0.5)\n",
    "\n",
    "ax[1].scatter(X_spca[y == 0, 0], np.zeros((50, 1)) + 0.02,\n",
    "              color='red', marker='^', alpha=0.5)\n",
    "ax[1].scatter(X_spca[y == 1, 0], np.zeros((50, 1)) - 0.02,\n",
    "              color='blue', marker='o', alpha=0.5)\n",
    "\n",
    "ax[0].set_xlabel('PC1')\n",
    "ax[0].set_ylabel('PC2')\n",
    "ax[1].set_ylim([-1, 1])\n",
    "ax[1].set_yticks([])\n",
    "ax[1].set_xlabel('PC1')\n",
    "\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_13.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_kpca = rbf_kernel_pca(X, gamma=15, n_components=2)\n",
    "\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(7, 3))\n",
    "ax[0].scatter(X_kpca[y==0, 0], X_kpca[y==0, 1], \n",
    "            color='red', marker='^', alpha=0.5)\n",
    "ax[0].scatter(X_kpca[y==1, 0], X_kpca[y==1, 1],\n",
    "            color='blue', marker='o', alpha=0.5)\n",
    "\n",
    "ax[1].scatter(X_kpca[y==0, 0], np.zeros((50, 1))+0.02, \n",
    "            color='red', marker='^', alpha=0.5)\n",
    "ax[1].scatter(X_kpca[y==1, 0], np.zeros((50, 1))-0.02,\n",
    "            color='blue', marker='o', alpha=0.5)\n",
    "\n",
    "ax[0].set_xlabel('PC1')\n",
    "ax[0].set_ylabel('PC2')\n",
    "ax[1].set_ylim([-1, 1])\n",
    "ax[1].set_yticks([])\n",
    "ax[1].set_xlabel('PC1')\n",
    "\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_14.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example 2: Separating concentric circles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.datasets import make_circles\n",
    "\n",
    "X, y = make_circles(n_samples=1000, random_state=123, noise=0.1, factor=0.2)\n",
    "\n",
    "plt.scatter(X[y == 0, 0], X[y == 0, 1], color='red', marker='^', alpha=0.5)\n",
    "plt.scatter(X[y == 1, 0], X[y == 1, 1], color='blue', marker='o', alpha=0.5)\n",
    "\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_15.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scikit_pca = PCA(n_components=2)\n",
    "X_spca = scikit_pca.fit_transform(X)\n",
    "\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(7, 3))\n",
    "\n",
    "ax[0].scatter(X_spca[y == 0, 0], X_spca[y == 0, 1],\n",
    "              color='red', marker='^', alpha=0.5)\n",
    "ax[0].scatter(X_spca[y == 1, 0], X_spca[y == 1, 1],\n",
    "              color='blue', marker='o', alpha=0.5)\n",
    "\n",
    "ax[1].scatter(X_spca[y == 0, 0], np.zeros((500, 1)) + 0.02,\n",
    "              color='red', marker='^', alpha=0.5)\n",
    "ax[1].scatter(X_spca[y == 1, 0], np.zeros((500, 1)) - 0.02,\n",
    "              color='blue', marker='o', alpha=0.5)\n",
    "\n",
    "ax[0].set_xlabel('PC1')\n",
    "ax[0].set_ylabel('PC2')\n",
    "ax[1].set_ylim([-1, 1])\n",
    "ax[1].set_yticks([])\n",
    "ax[1].set_xlabel('PC1')\n",
    "\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_16.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_kpca = rbf_kernel_pca(X, gamma=15, n_components=2)\n",
    "\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(7, 3))\n",
    "ax[0].scatter(X_kpca[y == 0, 0], X_kpca[y == 0, 1],\n",
    "              color='red', marker='^', alpha=0.5)\n",
    "ax[0].scatter(X_kpca[y == 1, 0], X_kpca[y == 1, 1],\n",
    "              color='blue', marker='o', alpha=0.5)\n",
    "\n",
    "ax[1].scatter(X_kpca[y == 0, 0], np.zeros((500, 1)) + 0.02,\n",
    "              color='red', marker='^', alpha=0.5)\n",
    "ax[1].scatter(X_kpca[y == 1, 0], np.zeros((500, 1)) - 0.02,\n",
    "              color='blue', marker='o', alpha=0.5)\n",
    "\n",
    "ax[0].set_xlabel('PC1')\n",
    "ax[0].set_ylabel('PC2')\n",
    "ax[1].set_ylim([-1, 1])\n",
    "ax[1].set_yticks([])\n",
    "ax[1].set_xlabel('PC1')\n",
    "\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_17.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Projecting new data points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.spatial.distance import pdist, squareform\n",
    "from scipy import exp\n",
    "from scipy.linalg import eigh\n",
    "import numpy as np\n",
    "\n",
    "def rbf_kernel_pca(X, gamma, n_components):\n",
    "    \"\"\"\n",
    "    RBF kernel PCA implementation.\n",
    "\n",
    "    Parameters\n",
    "    ------------\n",
    "    X: {NumPy ndarray}, shape = [n_examples, n_features]\n",
    "        \n",
    "    gamma: float\n",
    "      Tuning parameter of the RBF kernel\n",
    "        \n",
    "    n_components: int\n",
    "      Number of principal components to return\n",
    "\n",
    "    Returns\n",
    "    ------------\n",
    "     alphas: {NumPy ndarray}, shape = [n_examples, k_features]\n",
    "       Projected dataset \n",
    "     \n",
    "     lambdas: list\n",
    "       Eigenvalues\n",
    "\n",
    "    \"\"\"\n",
    "    # Calculate pairwise squared Euclidean distances\n",
    "    # in the MxN dimensional dataset.\n",
    "    sq_dists = pdist(X, 'sqeuclidean')\n",
    "\n",
    "    # Convert pairwise distances into a square matrix.\n",
    "    mat_sq_dists = squareform(sq_dists)\n",
    "\n",
    "    # Compute the symmetric kernel matrix.\n",
    "    K = exp(-gamma * mat_sq_dists)\n",
    "\n",
    "    # Center the kernel matrix.\n",
    "    N = K.shape[0]\n",
    "    one_n = np.ones((N, N)) / N\n",
    "    K = K - one_n.dot(K) - K.dot(one_n) + one_n.dot(K).dot(one_n)\n",
    "\n",
    "    # Obtaining eigenpairs from the centered kernel matrix\n",
    "    # scipy.linalg.eigh returns them in ascending order\n",
    "    eigvals, eigvecs = eigh(K)\n",
    "    eigvals, eigvecs = eigvals[::-1], eigvecs[:, ::-1]\n",
    "\n",
    "    # Collect the top k eigenvectors (projected examples)\n",
    "    alphas = np.column_stack([eigvecs[:, i]\n",
    "                              for i in range(n_components)])\n",
    "\n",
    "    # Collect the corresponding eigenvalues\n",
    "    lambdas = [eigvals[i] for i in range(n_components)]\n",
    "\n",
    "    return alphas, lambdas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/sebastian/miniconda3/lib/python3.7/site-packages/ipykernel_launcher.py:37: DeprecationWarning: scipy.exp is deprecated and will be removed in SciPy 2.0.0, use numpy.exp instead\n"
     ]
    }
   ],
   "source": [
    "X, y = make_moons(n_samples=100, random_state=123)\n",
    "alphas, lambdas = rbf_kernel_pca(X, gamma=15, n_components=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.8713, 0.0093])"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_new = X[25]\n",
    "x_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.0788])"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_proj = alphas[25] # original projection\n",
    "x_proj"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.0788])"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def project_x(x_new, X, gamma, alphas, lambdas):\n",
    "    pair_dist = np.array([np.sum((x_new - row)**2) for row in X])\n",
    "    k = np.exp(-gamma * pair_dist)\n",
    "    return k.dot(alphas / lambdas)\n",
    "\n",
    "# projection of the \"new\" datapoint\n",
    "x_reproj = project_x(x_new, X, gamma=15, alphas=alphas, lambdas=lambdas)\n",
    "x_reproj "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(alphas[y == 0, 0], np.zeros((50)),\n",
    "            color='red', marker='^', alpha=0.5)\n",
    "plt.scatter(alphas[y == 1, 0], np.zeros((50)),\n",
    "            color='blue', marker='o', alpha=0.5)\n",
    "plt.scatter(x_proj, 0, color='black',\n",
    "            label='Original projection of point X[25]', marker='^', s=100)\n",
    "plt.scatter(x_reproj, 0, color='green',\n",
    "            label='Remapped point X[25]', marker='x', s=500)\n",
    "plt.yticks([], [])\n",
    "plt.legend(scatterpoints=1)\n",
    "\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_18.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Kernel principal component analysis in scikit-learn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.decomposition import KernelPCA\n",
    "\n",
    "X, y = make_moons(n_samples=100, random_state=123)\n",
    "scikit_kpca = KernelPCA(n_components=2, kernel='rbf', gamma=15)\n",
    "X_skernpca = scikit_kpca.fit_transform(X)\n",
    "\n",
    "plt.scatter(X_skernpca[y == 0, 0], X_skernpca[y == 0, 1],\n",
    "            color='red', marker='^', alpha=0.5)\n",
    "plt.scatter(X_skernpca[y == 1, 0], X_skernpca[y == 1, 1],\n",
    "            color='blue', marker='o', alpha=0.5)\n",
    "\n",
    "plt.xlabel('PC1')\n",
    "plt.ylabel('PC2')\n",
    "plt.tight_layout()\n",
    "# plt.savefig('images/05_19.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "Readers may ignore the next cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[NbConvertApp] Converting notebook ch05.ipynb to script\n",
      "[NbConvertApp] Writing 28174 bytes to ch05.py\n"
     ]
    }
   ],
   "source": [
    "! python ../.convert_notebook_to_script.py --input ch05.ipynb --output ch05.py"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  },
  "toc": {
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
